Breaking the confinement of fixed nodes: A causality-guided adaptive and interpretable graph neural network architecture
Graph neural networks (GNNs) have significantly advanced the processing of graph-
structured data, where objects exhibit complex relationships and interdependencies. The …
structured data, where objects exhibit complex relationships and interdependencies. The …
Nonlinear Matrix Factorization With Cognitive Opinion Formation for Social Recommendation
Recommender systems continuously strive to recommend items that the users potentially
like accurately. Most recommender systems assume that latent user preferences and item …
like accurately. Most recommender systems assume that latent user preferences and item …
Cascading graph contrastive learning for multi-behavior recommendation
J Yang, X Li, B Li, L Tian, B Xu, Y Chen - Neurocomputing, 2024 - Elsevier
Traditional recommendation techniques often prioritize target behavior in practical
recommendation scenarios (eg, follow, play and buy). However, these approaches suffer …
recommendation scenarios (eg, follow, play and buy). However, these approaches suffer …
Robust Preference-Guided based Disentangled Graph Social Recommendation
GF Ma, XH Yang, Y Zhou, H Long… - … on Network Science …, 2024 - ieeexplore.ieee.org
Social recommendations introduce additional social information to capture users' potential
item preferences, thereby providing more accurate recommendations. However, friends do …
item preferences, thereby providing more accurate recommendations. However, friends do …
基于图重构的社交知识推荐.
张馨月， 高辉 - Application Research of Computers/Jisuanji …, 2024 - search.ebscohost.com
现有推荐模型大多聚焦于显式地构建用户和物品的联系, 忽视了对图结构高阶全局特性的建模,
对用户隐式兴趣的挖掘不足. 因此, 提出了一种基于图重构的社交知识推荐模型 …
对用户隐式兴趣的挖掘不足. 因此, 提出了一种基于图重构的社交知识推荐模型 …